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Doug Tygar's class of "ethical hackers" learns to wage cyberwar

Prof. Doug Tygar and his CS 194 Cybewar class are the focus of a New Yorker article titled "At Berkeley, a New Generation of “Ethical Hackers” Learns to Wage Cyberwar." The students have teamed up with the white hat hackers at HackerOne, a vulnerability coordination and bug bounty platform. Companies, organizations, and government agencies use HackerOne to solicit help identifying vulnerabilities in their products––or, as Tygar put it, “subject themselves to the indignity of having undergraduate students try to hack them.” Junior Vy-An Phan decided to focus on various secretary-of-state Web sites around the country, which house tools central to the electoral process—voter registration, ballot measures, candidate information, Election Day guidelines. She has already found eight bugs spread across four sites. “I could trick someone into registering for the wrong party, or not registering at all,” Phan said.

Embodied Intelligence raises $7M in seed round

Start-up Embodied Intelligence, founded by Prof. Pieter Abbeel and his grad students Peter Chen, Rocky Duan, and Tianhao Zhang, raised $7M in a seed round yesterday led by venture capital firm Amplify Partners. VC firms Lux Capital, SV Angels, FreeS, 11.2 Capital, and A. Capital also supplied capital. Embodied Intelligence is building AI software to enable robots to learn tasks performed by the user via a virtual reality headset. It claims existing robots will be compatible with the "robot brain," which would supplant coding scripts tailored to each task. Embodied will use the seed capital to write its first robotics applications.

Students help debunk fake news surrounding Texas shooting

EECS junior Rohan Phadte and fellow student Ash Bhat launched their Chrome browser extension, Botcheck.me, on Halloween and it is already proving invaluable. The app determines whether news posts on Twitter likely came from real people or were generated by a bot. When an armed gunman attacked the congregants of a Texas church this weekend, all legitmate news accounts agreed that neither race nor religion appeared to play a role. But a barrage of bots immediately started spreading rumors that the shooter had recently converted to Islam or was a member of Antifa. According to a simple random sample of 1,500 political propaganda Twitter bots the students posted on their site, #texaschurchmassacre was the bot world’s third favorite hashtag on Monday, after #maga and #antifa.

Students learn to think like hackers for 'cyberwar' course

CS students enrolled in CS 194, an experimental “cyberwar” course led by Prof. Doug Tygar, have joined forces with the white hat hackers at HackerOne, a vulnerability coordination and bug bounty platform. This is the first time that HackerOne--which connects hackers with tech companies, private businesses and federal agencies to hunt for vulnerabilities--has partnered with a university. Students are gaining real-world cyberwar experience. “Unless students can learn to ‘think like a hacker,’ they will not be able to effectively defend systems” says Tygar.

EECS-affiliated startup uses virtual reality to show robots how to perform

The start-up Embodied Intelligence and its founders, Prof. Pieter Abbeel and grad students Peter Chen, Rocky Duan, and Tianhao Zhang, are the focus of two news articles: one from the New York Times titled "A.I. Researchers Leave Elon Musk Lab to Begin Robotics Start-Up," and one from Berkeley News titled "Berkeley startup to train robots like puppets." The start-up is backed by $7 million in funding from Amplify Partners and other investors and will specialize in complex algorithms that allow machines to learn new tasks on their own through extreme trial and error. The researchers are augmenting the algorithms with a wide range of techniques, like using virtual reality tools to show a robot how to perform a task--translating the movements into digital data. “With our advances in machine learning, we can write a piece of software once — machine learning code that enables the robot to learn — and then when the robot needs to be equipped with a new skill, we simply provide new data.” Abbeel explains.

A UC Berkeley/UC Riverside research group that includes Prof. Jeffrey Bokor, Prof. Sayeef Salahuddin, postdoc Charles-Henri Lambert, postdoctoral fellow Jon Gorchon, and EE graduate student Akshay Pattabi have developed a new, ultrafast method for electrically controlling magnetism in certain metals, a breakthrough that could lead to greatly increased performance and more energy-efficient computer memory and processing technologies. Their findings are published in both Science Advances (Vol. 3, No. 49, Nov. 3, 2017) under the title Ultrafast magnetization reversal by picosecond electrical pulses and Applied Physics Letters (Vol. III, No. 4, July 24, 2017) under the title Single shot ultrafast all optical magnetization switching of ferromagnetic Co/Pt multilayers. “The development of a non-volatile memory that is as fast as charge-based random-access memories could dramatically improve performance and energy efficiency of computing devices,” says Bokor. “That motivated us to look for new ways to control magnetism in materials at much higher speeds than in today’s MRAM.”

A paper co-authored by postdoc Pramod Subramanyan, grad student Rohit Sinha, alumnus Ilia Lebedev (B.S. '10), alumnus and MIT Prof. Srinivas Devadas (M.S. '86/Ph.D. '88), and EECS Prof. Sanjit A. Seshia has won Best Paper Award at the 2017 ACM Conference on Computer and Communications Security (CCS). The paper, A Formal Foundation for Secure Remote Execution of Enclaves, introduces a formal modeling and verification methodology for secure remote execution based on the notion of a trusted abstract platform. CCS is the flagship annual conference of the Special Interest Group on Security, Audit and Control (SIGSAC) of the Association for Computing Machinery (ACM).

Amit Kumar and Accel launch Accel Scholars EECS mentorship program

EECS alumnus Amit Kumar (B.S. '03) and the venture firm Accel are launching a mentorship program called Accel Scholars to support EECS undergraduates. Accel will work with a select group of students over the course of a year, hosting networking dinners and also guaranteeing the students an internship at a portfolio company. Kumar initiated the program because he felt there wasn’t enough career guidance for students at Berkeley and that venture firms that ignore the ecosystem are missing out. Chair James Demmel says EECS is grateful for the opportunity to “partner with Accel and its network to provide a fast-track for an exceptionally talented and diverse cohort of undergraduates, who will benefit from mentorship by Accel but also by and from one another.”

Rohan Phadte and Ash Bhat are doing what Twitter won't

EECS undergraduate Rohan Phadte and Interdisciplinary Studies major Ash Bhat are the subjects of a Wired article titled "The College Kids Doing What Twitter Won't," about their creation of a Google Chrome browser extension that checks whether Twitter profiles are bots. It describes the genesis of their partnership, which they call RoBhat Labs, and theirefforts to stop the proliferation of fake Twitter accounts from flooding the internet with propaganda. It also highlights the roles played by CS Assistant Prof. Joseph Gonzalez and the class Data Science 100.

Caffe team wins Everingham Prize at ICCV 2017

The Caffe team researchers ('13 alumnus and current GSR Yangqing Jia, grad student Evan Shelhamer, '17 alumnus Jeff Donahue, '15 alumnus Sergey Karayev, grad student Jonathan Long, former postdocs Ross Girshick and Sergio Guadarrama, and Prof. in Residence Trevor Darrell) have been awarded the Mark Everingham Prize at the International Conference on Computer Vision (ICCV) 2017. Caffe is a deep learning framework made with expression, speed, and modularity in mind, developed by Berkeley AI Research (BAIR) and by community contributors. The Everingham Prize is bestowed by the IEEE technical committee on Pattern Analysis and Machine Intelligence (PAMI) and is given to individuals or groups "who have made a selfless contribution of significant benefit to other members of the computer vision community." The Caffe team won "for providing an open-source deep learning framework that enabled the community to use, train and share deep convolutional neural networks. Caffe has had a huge impact, both academic and commercial. "